Computation of the locus crossing point location of MC circuit

In this paper, the crossing point property of the i-v hysteresis curve in a memristor-capacitor （MC） circuit is analyzed. First, the ideal passive memristor on the crossing point property of i-v hysteresis curve is studied. Based on the analysis, the analytical derivation with respect to the crossing point location of MC circuit is given. Then the example of MC with linear memristance-versus-charge state map is demonstrated to discuss the drift property of cross-point location, caused by the frequency and capacitance value.     

Memristance controlling approach based on modification of linear M–q curve

The memristor has broad application prospects in many fields, while in many cases, those fields require accurate impedance control. The nonlinear model is of great importance for realizing memristance control accurately, but the im- plementing complexity caused by iteration has limited the actual application of this model. Considering the approximate linear characteristics at the middle region of the memristance-charge （M-q） curve of the nonlinear model, this paper pro- poses a memristance controlling approach, which is achieved by linearizing the middle region of the M-q curve of the nonlinear memristor, and establishes the linear relationship between memristances M and input excitations so that it can realize impedance control precisely by only adjusting input signals briefly. First, it analyzes the feasibility for linearizing the middle part of the M-q curve of the memristor with a nonlinear model from the qualitative perspective. Then, the lin- earization equations of the middle region of the M-q curve is constructed by using the shift method, and under a sinusoidal excitation case, the analytical relation between the memristance M and the charge time t is derived through the Taylor series expansions. At last, the performance of the proposed approach is demonstrated, including the linearizing capability for the middle part of the M-q curve of the nonlinear model memristor, the controlling ability for memristance M, and the influence of input excitation on linearization errors.